Avoidance of confusion between Similar looking Characters in Neuro-fuzzy based License Plate Recognition

Abstract—This paper presents a new methodology for the image segmentation and character recognition from standard Indian License number plates. Firstly it gets input of the segmented characters that is partitioned by our pixel Clustering partitioning method, in which we eliminate similar part from the character and match it by judging template and return identified character. This partitioning may be applied horizontally or vertically. Decision that the characters are partitioned horizontally or vertically depends on their subgroup. Before sub grouping we have to group the characters on the basis of the number of holes in it and then we subgroup on the basis of some similar features like | , / , \ , _ , ( , - , etc. If we have alphabet T and I where similar portion is I then both will go to same subgroup and we partition it horizontally. This method eliminates the problem of confusion between similar looking elements like C, G and T, I, 1, J etc by exploiting the small but important differences among them.